Multi-objective optimization based real-time control for PEV hybrid energy management systems

Abstract

Battery/ultracapacitor (UC) hybrid energy management systems (HEMS) have been introduced into plug-in electric vehicles (PEVs), mainly to enhance the power density and energy density performances of the onboard energy storage systems. In HEMS, a control strategy is required to distribute power among different energy sources. In this paper, a novel real-time control strategy is proposed for use in PEV onboard HEMS. A cost function is formulated for each component of the HEMS to illustrate the respective loss. The entire problem is then rendered into a multi-objective optimization problem, which seeks to minimize those three cost functions. Weighted-sum method and no-preference method are employed to solve this optimization problem. The solved optimized strategy is implemented and simulated in Advanced VehIcle SimulatOR (ADVISOR) to validate the concept. Results show that the proposed real-time control strategy owns the advantages of prolonged lifetime of the battery, extended PEV driving distance and enhanced system response.